The structural implications of measurement error in sociometry
The structural implications of measurement error in sociometry
复制标题
社会测量学中测量误差的结构影响
DOI：
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发表时间：
1973
期刊：
影响因子：
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通讯作者：
S. Leinhardt
中科院分区：
文献类型：
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作者：
P. Holland;S. Leinhardt
测量误差，任何经验数据收集技术的内在质量，讨论的背景下，社会计量数据。长期以来，这些数据一直被认为具有表面有效性，并且是任何小规模社会系统情感结构研究中的首选数据。然而，有人认为，虽然社会计量分析的方法已经变得越来越复杂，但它们未能产生明确的结果，因为它们没有区分结构复杂性和测量误差。通过对越来越复杂的例子的讨论，说明了大多数社会计量数据的失真特征。这种扭曲是由社会计量测试的形式引入的，它不会通过开发越来越复杂的结构模型或丢弃一些数据来消除。相反，当有关特定关系网络的性质的问题被提出时，需要比通常可用的数据质量高得多的数据。
Measurement error, an inherent quality of any empirical data collection technique, is discussed in the context of sociometric data. These data have long been assumed to possess face validity and to be the data of choice in any study of the sentiment structure of small scale social systems. However, it is argued that while methods of sociometric analysis have become increasingly more sophisticated they have failed to yield unequivocal results because they do not distinguish structural complexity from measurement error. Through a discussion of increasingly more complex examples the distortion laden character of most sociometric data is illustrated. This distortion is introduced by the formalities of the sociometric test and it will not be removed by developing increasingly more sophisticated structural models or throwing out some of the data. Instead, when issues concerning the nature of specific relational networks are raised data of much higher quality than those which are commonly available are required....